Factors Influencing the Acceptance of Healthcare Information Technologies: A Meta-Analysis

Chong, A.; Blut, M.; Zheng, S.

Abstract

Healthcare information technologies (HIT) can address several challenges faced by healthcare systems. To benefit from the advantages HIT offer, users must first accept them. This meta-analysis synthesizes previous research on HIT acceptance. It uses data from 214 independent samples reported in 193 articles and 83,619 technology users from 33 countries. The study contributes to the HIT literature by (1) synthesizing the empirical findings on technology acceptance factors and combining them in a comprehensive model, (2) testing the mediating mechanisms of health technology acceptance, and (3) examining contextual differences. The study finds that HIT acceptance depends on various predictors proposed by the technology acceptance model and the unified theory of acceptance and use of technology. These factors displayed strong indirect effects through effort expectancy, perceptions of the technology, performance expectancy, and attitudes toward using HIT. Studies overlooking these effects may underestimate the importance of various acceptance factors. Finally, the results suggest that technology acceptance varies across healthcare technologies (remote information systems [IS], wearables), users (staff/patients, age, voluntariness, experience), and locations (hospitals, healthcare systems, life expectancy in country). We also provide IS managers with guidance for improving technology acceptance in the healthcare industry to ensure efficient, high-quality services.

Citation

Chong, A., Blut, M., & Zheng, S. (2022). Factors Influencing the Acceptance of Healthcare Information Technologies: A Meta-Analysis. Information and Management, 59(3), Article 103604. https://doi.org/10.1016/j.im.2022.103604

• Journal Article Type: Article
• Acceptance Date: Jan 24, 2022
• Online Publication Date: Feb 1, 2022
• Publication Date: 2022-04
• Deposit Date: Jan 27, 2022
• Publicly Available Date: Feb 2, 2024
• Journal: Information and Management
• Print ISSN: 0378-7206
• Electronic ISSN: 1872-7530
• Publisher: Elsevier
• Peer Reviewed: Peer Reviewed
• Volume: 59
• Issue: 3
• Article Number: 103604
• DOI: https://doi.org/10.1016/j.im.2022.103604
• Public URL: https://durham-repository.worktribe.com/output/1218542